, 1998 and Abeles and Gat, 2001), were found to reoccur IDH inhibition within minicolumns

with a higher rate than chance as the respective assemblies were repeatedly activated. The coexistence of structured multi-neuronal firing with highly irregular single neuron firing accompanied by gamma oscillations might seem counterintuitive at first sight, especially if each cell connects to other cells within the same assembly (minicolumn) randomly with the same probability. The structured firing could however be understood from the perspective of the balanced currents that yield spiking irregularity at a single-cell level in oscillatory networks (Brunel and Wang, 2003 and Lundqvist et al., 2010). In this regime, small perturbations in excitability, either in spatial or in temporal domain, have much stronger impact on spike timing compared to a regime with high net excitation. Therefore the effect that some cells by chance are acting as hubs in the recurrent network, or that some cells are unidirectionally connected to selleck chemical others, might emerge in the spiking patterns in balanced networks. Here, the nested oscillations with cells having distinct preferred firing phases also contributed to the higher number of precise firing sequences. It should be stressed that despite the fact that individual cell assemblies were replayed at relatively regular intervals, the reoccurrence

of specific spatiotemporal spike patterns did not follow the same trend. Nested oscillations have also been identified in simulations of minimalistic hippocampal networks (White et al., 2000, Tiesinga et al., 2001 and Rotstein et al., 2005) and complex

cortical bottom-up networks (Neymotin et al., 2011). In addition, Kramer et al. (2008) have recently examined Amino acid interactions between oscillations in separate cortical layers and demonstrated in a simplified model the occurrence of lower-beta activity due to period concatenation of simultaneousfaster rhythms. Our focus was to investigate the phenomenon of an oscillatory hierarchy in a functional memory network. We showed that the recurrent connectivity storing attractor memory patterns, hypothesized to arise from learning, could provide a foundation for the coexistence of oscillations in multiple bands and specific cross-frequency effects. To date, computational studies have instead stressed the importance of intrinsic cell properties (Tiesinga et al., 2001, Rotstein et al., 2005 and Neymotin et al., 2011), inhibitory networks (White et al., 2000, Tiesinga et al., 2001 and Rotstein et al., 2005) and layer interactions (Kramer et al., 2008) as the key underlying mechanisms. Our findings do not contradict these studies, as the origins of oscillations in single-frequency bands in our network can be linked to these studies, but rather shed new light upon potential functional implications of nested oscillatory dynamics.